Saturday, May 03, 2008

Thursday I made a stop at the supermarket during the middle of the day, middle of the week – no market research on senior citizens this time, just a quick trip for things we needed to make it until Saturday. At the checkout I ended up with: navel oranges, apples, cilantro, lettuce, cukes, tofu, eggs, cheese, two kinds of bread, organic peanut butter, specialty crackers, macaroni and cheese, yogurt, and six different kinds of chocolate bars. Only about four things were on my grocery list. Some were impulse buys – but not perhaps what you'd think. All that chocolate was on the list. Some of the produce was not.

But what can you tell about my consuming and shopping future from just this one cart? (Here’s one hint: almost everything, including the crackers, are brands I buy all the time. The only variation was the chocolate – I buy it every week, but always try new kinds . Today they actually had new varieties on sale!). How would you characterize my purchases? What can they tell you about brand loyalty (some), consistency (a lot), and general purchasing trends (produce as impulse buy!!) ? Looking at shopping carts is a tried and true research method, and is always a staple of larger shopper marketing programs. It’s certainly better than consumer surveys. CPG News recently reported (as noted in this RetailWire BrainTrust post) that:

Catalina Marketing has spent two years examining 250 million shopping baskets weekly from 130 million separate shopper identifications. The goal is to probe the gap between what shoppers say they buy in surveys and what they actually purchase.

I probably wouldn’t mention those chocolate bars in a survey. But the shopping cart in isolation – one day, one cart – is as problematic as the shopping survey. One of the things I’ve been studying for years is everyday meals – how frequently people eat at home, what they cook, what they get as take out or prepared meals, who they eat with. The most important thing I’ve learned is that people live their lives according to patterns, but one slice won’t give you even the slightest idea what any given day might look like. For example, the Sunday dinner is different from but dependent on its contrast with the weekday supper, the holiday meal captures the extremes, and there are other punctuation marks all along the way.

Shopping carts are going to reflect patterning, too. Mine was a Wednesday cart on a week when someone had done the week’s shopping on the previous weekend. But we eat a lot of produce and always run out midweek. I’d also exhausted my chocolate supply, which sometimes (but not always) happens too. But if you looked at our cart over a month, you would get a very different picture – where do we run to for a loaf of bread or eggs? How much do we shop at little local markets or at big supersavers like Costco? What happens on a week when we do get down to the Saturday morning farm and specialty markets (the Strip District, for those who know Pittsburgh). How much did we eat out this week? Who is doing the cooking and who is being fed (the mac and cheese was for my daughter’s friend, who never eats anything else I make)?

Certainly many market researchers worry about whether people will tell “truth,” but truth is not in a snapshot. Rather it's in multiple images, over time and place (the whole pie!). More importantly, shopping carts are the repositories for later use. If we don’t find out how people are making use of the products, we don’t understand their purchases. Shopping cart data may be rich, but it's ultimately less useful if we don't map patterns of food use along with food purchases.

Still, watching shopping carts is particularly important right now as two consumer trends are butting up right against each other: one, the growing concern with organic, natural, and “green” products (which still tend to be a bit more expensive in most markets) and two, the rising cost of food in general, which tends to push people more towards bargains, coupons, and other sale items.

Mapping patterns seems like a lot of work, but without it, you’ve got tons of data and no anchoring scheme. The distinction between shopper and consumer is too simplistic to capture what’s going on (on Wed I was both and neither!!!). It also needs to be matched against what’s on sale, what’s out of stock, and what’s new in the store (seasonally, for example).

Shopping cart data needs to be put into a meaningful framework in order to make sense. If the data comes without questions and information about how the products are about to be used, all we know is what people have bought. There’s no insight into why.